cse373: data structures and algorithms lecture 1: introduction; adts; stacks/queues dan grossman...

CSE373: Data Structures and Algorithms

Lecture 1: Introduction; ADTs; Stacks/Queues

Dan Grossman

Fall 2013

2CSE373: Data Structures and Algorithms

Welcome!

We have 10 weeks to learn fundamental data structures and algorithms for organizing and processing information– “Classic” data structures / algorithms and how to analyze

rigorously their efficiency and when to use them– Queues, dictionaries, graphs, sorting, etc.

Today in class:• Introductions and course mechanics• What this course is about• Start abstract data types (ADTs), stacks, and queues

– Largely review

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Concise to-do list

See your “first-day handout”

In next 24-48 hours:• Adjust class email-list settings• Take homework 0 (worth 0 points) as Catalyst quiz• Read all course policies• Read/skim Chapters 1 and 3 of Weiss book

– Relevant to Homework 1, due next week– Will start Chapter 2 fairly soon

Possibly:• Set up your Java environment for Homework 1

http://courses.cs.washington.edu/courses/cse373/13au/

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Course staff

Instructor: Dan Grossman

TA: Luyi Lu

TA: Conrad Nied

TA: Nicholas Shahan

TA: Jasmine Singh

TA: Sam Wilson

Fall 2013

Dan: CSE Faculty for 10 years (omg!), loves teaching• Also loves to talk , you’ll surely learn lots of things about me

from class

Office hours, email, etc. on course web-page


Communication

• Course email list: [email protected]– Students and staff already subscribed– You must get announcements sent there– Fairly low traffic

• Course staff: [email protected] plus individual emails

• Discussion board– For appropriate discussions; TAs will monitor– Encouraged, but won’t use for important announcements

• Anonymous feedback link– For good and bad: if you don’t tell me, I don’t know

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Course meetings

• Lecture (Dan)– Materials posted, but take notes– Ask questions, focus on key ideas (rarely coding details)

• Optional meetings on Tuesday/Thursday afternoons– Will post rough agenda roughly a day or more in advance– Help on programming/tool background– Helpful math review and example problems– Again, optional but helpful– May cancel some later in course (experimental)

• Office hours– Use them: please visit me– Ideally not just for homework questions (but that’s great too)

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Course materials

• All lecture and section materials will be posted– But they are visual aids, not always a complete description!– If you have to miss, find out what you missed

• Textbook: Weiss 3rd Edition in Java– Good read, but only responsible for lecture/hw topics– 3rd edition improves on 2nd, but we’ll support the 2nd

• A good Java reference of your choosing?– Don’t struggle Googling for features you don’t understand?

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Computer Lab

• College of Arts & Sciences Instructional Computing Lab – http://depts.washington.edu/aslab/– Or your own machine

• Will use Java for the programming assignments

• Eclipse is recommended programming environment

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Course Work

• 6 homeworks (50%)– Most involve programming, but also written questions– Higher-level concepts than “just code it up”– First programming assignment due week from Friday

• Midterm #1 Friday October 18 (15%)• Midterm #2 Friday November 15 (15%)• Final exam: Tuesday December 10, 2:30-4:20 (20%)

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Collaboration and Academic Integrity

• Read the course policy very carefully– Explains quite clearly how you can and cannot get/provide

help on homework and projects

• Always explain any unconventional action on your part– When it happens, when you submit, not when asked

• I have promoted and enforced academic integrity since I was a freshman– I offer great trust but with little sympathy for violations– Honest work is the most important feature of a university

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Some details

• You are expected to do your own work– Exceptions (group work), if any, will be clearly announced

• Sharing solutions, doing work for, or accepting work from others is cheating

• Referring to solutions from this or other courses from previous quarters is cheating

• But you can learn from each other: see the policy

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Unsolicited advice

• Get to class on time!– Instructor pet peeve (I will start and end promptly)– First 2 minutes are much more important than last 2!– Midterms will prove beyond any doubt you are capable

• Learn this stuff– It is at the absolute core of computing and software– Falling behind only makes more work for you

• Have fun– So much easier to be motivated and learn

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Today in Class

• Course mechanics: Did I forget anything?

• What this course is about

• Start abstract data types (ADTs), stacks, and queues– Largely review

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Data Structures

• Introduction to Algorithm Analysis

• Lists, Stacks, Queues

• Trees, Hashing, Dictionaries

• Heaps, Priority Queues

• Sorting

• Disjoint Sets

• Graph Algorithms

• May have time for other brief exposure to topics, maybe parallelism

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Assumed background

• Prerequisite is CSE143

• Topics you should have a basic understanding of:– Variables, conditionals, loops, methods, fundamentals of

defining classes and inheritance, arrays, single linked lists, simple binary trees, recursion, some sorting and searching algorithms, basic algorithm analysis (e.g., O(n) vs O(n2) and similar things)

• We can fill in gaps as needed, but if any topics are new, plan on some extra studying

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What 373 is about

• Deeply understand the basic structures used in all software– Understand the data structures and their trade-offs– Rigorously analyze the algorithms that use them (math!)– Learn how to pick “the right thing for the job”– More thorough and rigorous take on topics introduced in

CSE143 (plus more new topics)

• Practice design, analysis, and implementation– The elegant interplay of “theory” and “engineering” at the

core of computer science

• More programming experience (as a way to learn)

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Goals

• Be able to make good design choices as a developer, project manager, etc.– Reason in terms of the general abstractions that come up in

all non-trivial software (and many non-software) systems• Be able to justify and communicate your design decisions

Dan’s take: – Key abstractions used almost every day in just about

anything related to computing and software– It is a vocabulary you are likely to internalize permanently

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Data structures

(Often highly non-obvious) ways to organize information to enable efficient computation over that information

A data structure supports certain operations, each with a:– Meaning: what does the operation do/return– Performance: how efficient is the operation

Examples:– List with operations insert and delete– Stack with operations push and pop

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Trade-offs

A data structure strives to provide many useful, efficient operations

But there are unavoidable trade-offs:– Time vs. space– One operation more efficient if another less efficient– Generality vs. simplicity vs. performance

We ask ourselves questions like:– Does this support the operations I need efficiently?– Will it be easy to use, implement, and debug?– What assumptions am I making about how my software will

be used? (E.g., more lookups or more inserts?)

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Terminology

• Abstract Data Type (ADT)– Mathematical description of a “thing” with set of operations

• Algorithm– A high level, language-independent description of a step-by-

step process

• Data structure– A specific organization of data and family of algorithms for

implementing an ADT

• Implementation of a data structure– A specific implementation in a specific language

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Example: Stacks

• The Stack ADT supports operations:– isEmpty: have there been same number of pops as pushes– push: takes an item– pop: raises an error if empty, else returns most-recently

pushed item not yet returned by a pop– … (possibly more operations)

• A Stack data structure could use a linked-list or an array or something else, and associated algorithms for the operations

• One implementation is in the library java.util.Stack

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Why useful

The Stack ADT is a useful abstraction because:• It arises all the time in programming (e.g., see Weiss 3.6.3)

– Recursive function calls– Balancing symbols (parentheses)– Evaluating postfix notation: 3 4 + 5 * – Clever: Infix ((3+4) * 5) to postfix conversion (see text)

• We can code up a reusable library

• We can communicate in high-level terms– “Use a stack and push numbers, popping for operators…”– Rather than, “create a linked list and add a node when…”

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The Queue ADT

• Operations

createdestroyenqueuedequeueis_empty

• Just like a stack except:– Stack: LIFO (last-in-first-out)– Queue: FIFO (first-in-first-out)

• Just as useful and ubiquitous

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F E D C Benqueue dequeueG A

Back Front


Circular Array Queue Data Structure

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// Basic idea only!enqueue(x) { Q[back] = x; back = (back + 1) % size }

// Basic idea only!dequeue() { x = Q[front]; front = (front + 1) % size; return x;}

b c d e fQ: 0 size - 1

front back

• What if queue is empty?– Enqueue?– Dequeue?

• What if array is full?• How to test for empty?• What is the complexity of

the operations?• Can you find the kth

element in the queue?


Linked List Queue Data Structure

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b c d e f

front back

// Basic idea only!enqueue(x) { back.next = new Node(x); back = back.next; }

// Basic idea only!dequeue() { x = front.item; front = front.next; return x;}

• What if queue is empty?– Enqueue?– Dequeue?

• Can list be full?• How to test for empty?• What is the complexity of

the operations?• Can you find the kth

element in the queue?


Circular Array vs. Linked List

Array:– May waste unneeded space

or run out of space– Space per element excellent– Operations very simple / fast– Constant-time access to kth

element

– For operation insertAtPosition, must shift all later elements– Not in Queue ADT

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This is stuff you should know after being awakened in the dark

List:– Always just enough space– But more space per element– Operations very simple / fast– No constant-time access to kth

element

– For operation insertAtPosition must traverse all earlier elements– Not in Queue ADT


The Stack ADT

Operations:

createdestroypushpoptopis_empty

Can also be implemented with an array or a linked list– This is Homework 1!– Like queues, type of elements is irrelevant

Fall 2013

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cse373: data structures and algorithms lecture 1: introduction; adts; stacks/queues dan grossman...

Documents

fundamental data structures

algorithms dan

course materials

algorithms lecture

course mechanics

course work

course webpage slide

course staff instructor